Elsevier

Accident Analysis & Prevention

Driving safety assessment for ride-hailing drivers

Highlights

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Utilize Big Data Analytics to place crash risk factors for ride-hailing drivers.

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Significant risk factors include passenger rating, long shifts, peak-hour driving.

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Employ Poisson Generalized Additive Model to accommodate nonlinear outcome.

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Use the SHAP method to assess the impact of risk factors.

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Operational characteristics are valuable for assessing ride-hailing driver crash take a chance.

Abstruse

Ride-hailing services, which have become increasingly prevalent in the last decade, provide an efficient travel mode by matching drivers and travelers via smartphone apps. Ride-hailing services enable millions of non-traditional taxi drivers to provide travel services, but may also raise safety concerns due to heterogeneity in the driver population. This written report evaluated crash risk factors for ride-hailing drivers, including driving history and ride-hailing operational characteristics, using a sample of 189,815 drivers. We utilized the Poisson generalized additive model to suit for the potential nonlinear human relationship between crash rate and adventure factors. Results showed that crash history, the percentage of long-shift bookings, driving distance, operations during meridian hours, years of beingness a ride-hailing commuter, and passenger rating were significantly associated with crash run a risk. Several factors showed nonlinear relationships with crash risk. Nosotros adopted the SHapley Additive exPlanation (SHAP) method to assess and visualize the bear upon of each gamble factor. The results indicated that passenger average rating, full driving distance, and crash history were the leading contributing factors. The findings of this study provide critical information for the development of safety countermeasures, driver education programs, as well every bit rubber regulations for the ride-hailing industry.

Keywords

Ride-hailing drivers

Crash take a chance factors

Operational characteristics

General condiment models

SHapley Additive explanation

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